Modern DNA sequencing has instituted a new era in human cytomegalovirus (HCMV) genomics. A key development has been the ability to determine the genome sequences of HCMV strains directly from clinical material. This involves the application of complex and often non-standardized bioinformatics approaches to analysing data of variable quality in a process that requires substantial manual intervention. To relieve this bottleneck, we have developed GRACy (Genome Reconstruction and Annotation of Cytomegalovirus), an easy-to-use toolkit for analysing HCMV sequence data. GRACy automates and integrates modules for read filtering, genotyping, genome assembly, genome annotation, variant analysis, and data submission. These modules were tested extensively on simulated and experimental data and outperformed generic approaches. GRACy is written in Python and is embedded in a graphical user interface with all required dependencies installed by a single command. It runs on the Linux operating system and is designed to allow the future implementation of a cross-platform version. GRACy is distributed under a GPL 3.0 license and is freely available at https://bioinformatics.cvr.ac.uk/software/ with the manual and a test dataset.

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Understanding the intrahost evolution of viral populations has implications in pathogenesis, diagnosis and treatment, and has recently made impressive advances from developments in high-throughput sequencing. However, the underlying analyses are very sensitive to sources of bias, error and artefact in the data, and it is important that these are addressed adequately if robust conclusions are to be drawn. The key factors include: (i) determining the number of viral strains present in the sample analysed; (ii) monitoring the extent to which the data represent these strains and assessing the quality of these data; (iii) dealing with the effects of cross-contamination; and (iv) ensuring that the results are reproducible. We investigated these factors by generating sequence datasets, including biological and technical replicates, directly from clinical samples obtained from a small cohort of patients who had been infected congenitally with the herpesvirus human cytomegalovirus, with the aim of developing a strategy for identifying high-confidence intrahost variants. We found that such variants were few in number and typically present in low proportions, and concluded that human cytomegalovirus exhibits a very low level of intrahost variability. In addition to clarifying the situation regarding human cytomegalovirus, our strategy has wider applicability to understanding the intrahost variability of other viruses.